Investigating EFL Learners’ Perceptions of Using AI to Enhance English Vocabulary Acquisition Based on The Technology Acceptance Model

Authors

  • Saleh Mohammad Alsakaker

    Department of English, College of Education, Majmaah University, Al-Majmaah 15362, Saudi Arabia

DOI:

https://doi.org/10.30564/fls.v7i2.8593
Received: 28 January 2025 | Revised: 20 February 2025 | Accepted: 21 February 2025 | Published Online: 26 February 2025

Abstract

The technological advancement of artificial intelligence (AI) has been shown to confer significant benefits in both technical and educational realms. Accordingly, the study aims to investigate learners’ perspectives on AI tools and attempts to assess which aspects of these tools are useful in improving vocabulary acquisition in a Saudi context. A structured questionnaire was designed based on the technology acceptance model (TAM) by using a quantitative method, and distributed to 112 undergraduate students from different colleges in Saudi Arabia, the majority of whom are Generation Z. The findings revealed that EFL learners generally hold a favorable view of AI tools for vocabulary acquisition, and gender differences were found to be statistically significant (p < 0.00) where female respondents report greater scores in terms of ease of use, usefulness, positive attitudes, and their intentions toward adoption. In addition, a person’s intention to adopt technology is primarily influenced by their assessment of its positive attitudes, followed by its simplicity and benefits of use. This study provides a deeper understanding about implementing AI tools to enhance EFL learners’ English vocabulary acquisition. The results can also nudge teachers and policymakers to further enhance their instructional strategies in ways that foster a more engaging and supportive environment for vocabulary growth.

Keywords:

Artificial Intelligence (AI); EFL Learners; EFL Vocabulary Learning; Technology Acceptance Model; Students’ Perceptions; Vocabulary Acquisition

References

[1] Nation, I.S.P. (ed.), 2001. Learning Vocabulary in Another Language, Vol. 10. Cambridge University Press: Cambridge, UK. pp. 126-132.

[2] Laufer, B., Hulstijn, J., 2001. Incidental vocabulary acquisition in a second language: The construct of task-induced involvement. Applied Linguistics. 22(1), 1-26. DOI: https://doi.org/10.1093/applin/22.1.1

[3] Haenlein, M., Kaplan, A., Tan, C.W. et al., 2019. Artificial intelligence (AI) and management analytics. Journal of Management Analytics. 6(4), 341-343. DOI: https://doi.org/10.1080/23270012.2019.1699876

[4] Oravec, J.A., 2018. Artificial intelligence, automation, and social welfare: Some ethical and historical perspectives on technological overstatement and hyperbole. Ethics and Social Welfare. 13(1), 18-32. DOI: https://doi.org/10.1080/17496535.2018.1512142

[5] Teo, T., Van Schaik, P., 2012. Understanding the intention to use technology by preservice teachers: An empirical test of competing theoretical models. International Journal of Human-Computer Interaction. 28(3), 178-188. DOI: https://doi.org/10.1080/10447318.2011.581892

[6] Cancino, M., Panes, J., 2021. The impact of Google Translate on L2 writing quality measures: Evidence from Chilean EFL high school learners. System. 98, 102464. DOI: https://doi.org/10.1016/j.system.2021.102464

[7] Oktadela, R., Elida, Y., Ismail, S., 2023. Improving English vocabulary through artificial intelligence (AI) chatbot application. Journal of English Language and Education. 8(2), 63-67.

[8] Stockwell, G., 2013. Mobile-assisted language learning. Contemporary Computer-Assisted Language Learning. 201-216.

[9] Peterson, M., 2017. The use of technology in teaching English as a foreign language. TESOL Quarterly. 51, 183–210.

[10] Kasneci, E., Sessler, K., Kuchemann, S., et al. ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences. 103, 102274. DOI: https://doi.org/10.1016/j.lindif.2023.102274

[11] Sholekhah, M.F., Fakhrurriana, R., 2023. The use of ELSA speak as a mobile-assisted language learning (MALL) towards EFL students pronunciation. JELITA: Journal of Education, Language Innovation, and Applied Linguistics. 2(2), 93-100. DOI: https://doi.org/10.37058/jelita.v2i2.7596

[12] Marzuki, Widiati, U., Rusdin, D., et al., 2023. The impact of AI writing tools on the content and organization of students' writing: EFL teachers' perspective. Cogent Education. 10(2), 2236469. DOI: https://doi.org/10.1080/2331186X.2023.2236469

[13] Dong, Y., 2023. Revolutionizing academic English writing through AI-powered pedagogy: practical exploration of teaching process and assessment. Journal of Higher Education Research. 4(2), 52. DOI: https://doi.org/10.32629/jher.v4i2.1188

[14] Peng, Z., Wang, X., Han, Q., et al., 2023. Storyfier: Exploring vocabulary learning support with text generation models. Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology; October 29-November 1, 2023; San Francisco, USA. pp. 1-16. DOI: https://doi.org/10.1145/3586183.3606786

[15] Derakhshan, A., Kruk, M., Mehdizadeh, M., et al., 2021. Boredom in online classes in the Iranian EFL context: Sources and solutions. System. 101, 102556. DOI: https://doi.org/10.1016/j.system.2021.102556

[16] Wang, Y., 2023. Probing into the boredom of online instruction among Chinese English language teachers during the Covid-19 pandemic. Current Psychology. 43(13), 12144-12158. DOI: https://doi.org/10.1007/s12144-022-04223-3

[17] Davis, F.D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 319-340. DOI: https://doi.org/10.2307/249008

[18] Shoufan, A., 2023. Exploring students' perceptions of ChatGPT: Thematic analysis and follow-up survey. IEEE Access. 11, 38805-38818. DOI: https://doi.org/10.1109/ACCESS.2023.3268224

[19] Davis, F.D., 1986. A technology acceptance model for empirically testing new end-user information systems [Doctoral Dissertation]. Massachusetts Institute of Technology: Cambridge, MA. pp. 1-291.

[20] Davis, F.D., Bagozzi, R.P., Warshaw, P.R., 1989. User acceptance of computer technology: A comparison of two theoretical models. Management Science. 35(8), 982-1003. DOI: https://doi.org/10.1287/mnsc.35.8.982

[21] Davis, F.D., 1993. User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies. 38(3), 475–487. DOI: https://doi.org/10.1006/imms.1993.1022

[22] Vo, A., Nguyen, H., 2024. Generative artificial intelligence and ChatGPT in language learning: EFL students' perceptions of technology acceptance. Journal of University Teaching and Learning Practice. 21(6), 199-218. DOI: https://doi.org/10.53761/fr1rkj58

[23] Maheshwari, G., 2024. Factors influencing students' intention to adopt and use ChatGPT in higher education: A study in the Vietnamese context. Education and Information Technologies. 29(10), 12167-12195. DOI: https://doi.org/10.1007/s10639-023-12333-z

[24] Losi, R.V., Putra, E., Ali, N., et al., 2024. Investigating artificial intelligence (AI) as a vocabulary learning tool: Students' perception to use ChatGPT. Proceeding International Conference on Religion, Science and Education. Vol. 3, pp. 561-566.

[25] Alharbi, K., Khalil, L., 2023. Artificial intelligence (AI) in ESL vocabulary learning: An exploratory study on students and teachers' perspectives. Migration Letters. 20(S12), 1030-1045.

[26] Jomaa, N., Attamimi, R., Al Mahri, M., 2024. Utilising artificial intelligence (AI) in vocabulary learning by EFL Omani students: The Effect of age, gender, and level of study. Forum for Linguistic Studies. 6(5), 171-186. DOI: https://doi.org/10.30564/fls.v6i5.6968

[27] Xiao, Y., Zhi, Y., 2023. An exploratory study of EFL learners' use of ChatGPT for language learning tasks: Experience and perceptions. Languages. 8(3), 212. DOI: https://doi.org/10.3390/languages8030212

[28] Rajendran, R., Banerjee, G., Pathak, D., et al., 2020. Impact of gender on motivation, engagement and interaction behavior in mobile assisted learning of English. 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT); July 6-July 9, 2020; Tartu, Estonia. pp. 230-232.

[29] Ebadi, S., Raygan, A., 2024. Investigating gender and experience effects on EFL learners' perceptions of Mobile assisted language learning. Technology Assisted Language Education. 2(1), 42-57. DOI: https://doi.org/10.22126/tale.2024.10638.1036

[30] Watson R., 2015. Quantitative research. Nursing Standard (Royal College of Nursing (Great Britain): 1987). 29(31), 44-48. DOI: https://doi.org/10.7748/ns.29.31.44.e8681

[31] Hernandez-de-Menendez, M., Escobar Díaz, C.A., Morales-Menendez, R., 2020. Educational experiences with Generation Z. International Journal on Interactive Design and Manufacturing (IJIDeM). 14(3), 847-859. DOI: https://doi.org/10.1007/s12008-020-00674-9

[32] Szymkowiak, A., Melović, B., Dabić, M., et al., 2021. Information technology and Gen Z: The role of teachers, the internet, and technology in the education of young people. Technology in Society. 65, 101565. DOI: https://doi.org/10.1016/j.techsoc.2021.101565

[33] Pallant, J., 2005. SPSS Survival Guide: A Step by Step Guide to Data Analysis Using SPSS for Windows, 3rd ed. Open University Press: New York, NY, USA. pp. 1-352.

[34] Lodge, J. M., de Barba, P., Broadbent, J., 2023. Learning with generative artificial intelligence within a network of co-regulation. Journal of University Teaching and Learning Practice. 20(7), 1-10. DOI: https://doi.org/10.53761/1.20.7.02

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How to Cite

Alsakaker, S. M. (2025). Investigating EFL Learners’ Perceptions of Using AI to Enhance English Vocabulary Acquisition Based on The Technology Acceptance Model. Forum for Linguistic Studies, 7(2), 1067–1077. https://doi.org/10.30564/fls.v7i2.8593

Issue

Vol. 7 , Iss. 2 (February 2025)

Article Type

Article

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Copyright © 2025 Saleh Mohammad Alsakaker

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This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.